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All about article topics, Memo’s secret weapon for readership insights

While the wealth of readership data that the Memo platform provides is certainly exciting, it is hard to extract those insights without having a way to “slice and dice” the numbers.

This is why our app assigns each article a “topic,” a label that provides an instant understanding of that article’s content.

Say you want to hone in on coverage about hiring and workplace benefits – perhaps to see which outlets get high readership on the subject, or how your share of readership compares to competing employers. You can filter by topic in the app, in this case Business News – Hiring, Wages, Benefits, and view readership stats specific to this theme.

Or conversely, if a topic is creating a lot of noise in your media coverage, you can filter it out to focus on the readership data most relevant to you. Pretty handy, right?

This month, we’re excited to release a new machine learning-powered classification system that improves both the categorization process and the topic taxonomy.

We’re calling this launch “universal topics.” And while a faster, more consistent topic schema might not seem flashy, I promise that it’s an actual game changer for surfacing deeper readership insights at scale. Here are the details:

Memo’s article topics are built for how PR & Comms teams view media coverage

Unlike tools that generalize the subject of a piece of content, Memo tags articles with topics that are relevant to the coverage categories PR & Comms teams think about every day. An article about the new iPhone wouldn’t just be “consumer electronics” or “iPhone.” Rather, Memo might label it Product – Launch – iPhone 14 so that the user knows this was product-related press about the launch of the new iPhone.

Universal topics follow a pattern of Primary Topic (all) – Secondary Topic (most) – Tertiary Topic (some). For many longtime Memo users, these labels will look familiar. Here’s how the taxonomy works:

First, every article is assigned one of 13 possible Primary Topics:

Advice: How-to, instructional, and advice-driven articles
Business News: Corporate news, earnings coverage, executive news, etc.
Celebrity: Celebrity interviews, paparazzi coverage, gossip, and partnerships
Content Availability: Coverage of how, when, and where to access content
Corporate Initiatives: ESG-related initiatives by companies
Deals & Promos: Sales announcements and promotional offers
Event: Summits, conferences, sporting events, awards ceremonies, etc.
Human Interest: Feature stories that portray people in an emotional way
Incident: Coverage of crimes, deaths, cyberattacks, etc.
Industry Trends: General industry news and commentary
Issue: Coverage of large societal issues
Product: News about a company’s products, including launches and reviews
Merchandising: Articles promoting the availability of retail goods

Content and industry nuances are captured with subtopics

Once the Primary Topic has been identified, most articles will receive a Secondary Topic, and some will receive a Tertiary Topic.

For certain Primary Topics, there are finite lists of corresponding Secondary Topics. All of the possible Secondary Topics for Business News, for example, are the following:

Business News – Earnings
Business News – Expansion
Business News – Hiring, Wages, Benefits
Business News – Leadership
Business News – M&A & Partnerships
Business News – Stocks & Markets
Business News – Thought Leadership

For other Primary Topics, there are infinite Secondary Topics. For instance, the primary topic Event has endless possibilities. In these cases, we use machine learning to pull out named entities that identify the specific event. An article that discusses the Emmy awards will be labeled Event – Emmy Awards. An article about the Academy Awards will be labeled Event – Academy Awards.

The primary topic Product is a combination of finite and infinite: the Secondary Topics are always either News, Review, Launch, or Roundup. Then we use entity extraction to pull a custom Tertiary Topic, typically the name of the product. So an article titled “Apple Launches iPhone 14 and 14 Plus” would be categorized as Product – Launch – iPhone 14.

The new topic schema enables easier readership analysis

A major benefit to the newly launched topic conventions is that the consistent structure makes it easier for brands to hone in on the coverage they care about for a given analysis.

In the iPhone example above, a brand like Apple could zoom in on iPhone 14 launch coverage to measure the readership of that campaign; they could look at the entire product news cycle for the iPhone 14 (the launch, product reviews, product promos, etc) to track readership over time; or they could compare all product launches across different devices to find the best outlets for the next device launch.

Imagines of Memo's readership dashboard filtering by different topics — *Consistent topic hierarchies and naming conventions make it easier for Memo users to filter for different types of coverage.*

Universal topics balance article fidelity with industry flexibility

Previously, topics were assigned at the brand level, meaning an article’s topic might differ across accounts.

By acknowledging that the topic of the article is a singular entity, universal topics create more value by prescribing an identity to that article, rather than assigning a topic in the context of the account’s dashboard.

The launch of Brand tags in our platform in 2021 (labels that indicate which brands are included in an article) removed the need to clarify the brand context in articles with topics. In the past, for instance, when an article only mentioned an account’s keywords in passing, Memo assigned it the topic Mention. While that is the context of the article in relation to the brand, it doesn’t actually tell us anything about the contents of the article!

With universal topics, each article’s topic is a direct representation of what that article is about. As described above, Secondary and Tertiary Topics provide more detailed entity information to make the topic relevant to the industry and brand. Altogether, this structure ensures consistency in reporting and allows Memo to provide deeper insights at scale.

Universal topics are also processed faster with new AI models

An added benefit to this launch is a standardized delivery time of the topic assignments. The granular customization at the brand level was possible with our legacy keyword-based topic assignment system, but it posed a hurdle as we migrated to more advanced, scalable machine learning models. And frankly, it took a long time to process.

Now, when you log into the dashboard first thing in the morning, all of the articles for the previous day will have a topic in addition to readership, every time! No more waiting for updates at 12pm EST or later.

We have been working hard over the past several months to revamp our topic system, and we are so excited to share these improvements with our clients. The scalability of this system paves the way for deeper and faster insights, reports, and product features – so this is just the beginning.

5 ways Comms orgs have upgraded media monitoring with Readership Emails

Every morning at 7:30, hundreds of people receive an email that tells them exactly how many people read their top press from the previous day.

On Wednesday afternoons, hundreds more get a snapshot of their most-read articles, publications, and topics from the previous week.

And each month, subscribers receive a broad summary of earned readership trends from the past 30 days.

All of this email reporting was automated in the past month, allowing us to offer upgraded media monitoring and measurement at scale. While Memo’s readership dashboard supports in-depth, exploratory trend analysis, we knew time-strapped Comms teams needed a way to quickly identify the stories, outlets, and competitors that deserve their attention. Readership Emails do exactly that, surfacing top-read mentions and high-level trends to spur further exploration.

Read on to learn more about daily, weekly, and monthly Readership Emails – and how PR & Comms teams are actioning this data every day.

#1: Use daily Readership Emails to surface big wins from current PR campaigns

Each morning, Memo automatically sends subscribers a daily digest of the previous day’s top-read headline and non-headline placements, as well as the most-read articles from the past three days.

This alert gives Comms teams an easy way to spot campaign wins – an article with great pull through reached a wide audience, a syndicated piece was highly read on regionals in your target market, etc. – and an straightforward report to forward to stakeholders.

#2: Use daily Readership Emails to monitor and mitigate potential crisis stories

Given that social media often refers less than 5% of an article’s traffic (and that social engagement is not predictably correlated to readership), social listening platforms are not reliable for assessing whether a negative story that hasn’t yet blown up could evolve into a crisis situation down the road. To paraphrase one Memo customer: “we already know when a crisis is really bad; we need readership for the simmering stories that may or may not bubble over.”

Monitoring readership on negative articles allows Comms teams to better allocate scarce resources and spokespeople to the trending stories that need their attention, while also providing time-saving clarification on the ones that completely flew under the radar.

#3: Get a pulse check on your share of voice with weekly Readership Emails

Weekly emailed reports include the most-read articles, outlets, and topics over the week for your brand and – for Memo customers who also track competitor readership – a competitive share of voice.

We report out SOV differently and, if we can be so bold, far more accurately. Instead of just looking at share of coverage, we also report share of readership, revealing the competitors that are generating meaningful engagement with their earned media, and through what stories. These weekly reports let Comms teams quickly see if a competitor’s SOV has reached a threshold that warrants further investigation.

And because weekly reports include competitors’ top-read press, subscribers can see what conversations are working for the competition and quickly devise a plan to participate before public interest moves on.

#4: Plan for the future with PR results reported in monthly Readership Emails

Monthly Readership Emails have all of the readership breakdowns included in weekly reports, but over the course of a whole month. Monthly reports give Comms teams an opportunity to step back and answer critical questions as they look to future campaigns. What outlets performed well for my brand that I should continue pitching? What outlets drove high readership for competitors that I should bump up to my priority list? What headlines and topics got the highest readership, and can I incorporate those angles into future campaigns? (All questions that would be impossible to answer with impressions, clip counts, or social listening alone.)

#5: Tie business outcomes to earned media performance with monthly Readership Emails

Monthly reports also provide an opportunity for Comms groups to pull out the performance metrics that marketing, analytics, and finance stakeholders would also want to incorporate into their own business analyses for the month. For example, providing the readership on reviews of a newly launched product to your Marketing team lets them incorporate apples-to-apples data from PR into their marketing mix model.

When one article gets 10,000 readers and another 1,000,000, it’s not enough to rely on clip counts alone. Readership Emails from Memo are fast becoming an essential part of the Comms tech stack – and they’re now available to all Memo customers.

Memo adds Detail Pages for in-depth views of article engagement

If readership lifts the veil on how earned media performed, Memo’s new Details Pages explain the why.

By surfacing article-level engagement data, Details Pages answer retrospective questions like how readers discovered an article and provide clarity on forward-looking decisions like which content to amplify.

Detail Pages provide Google Analytics-like insight into earned coverage

Just as marketers can use Google Analytics to monitor engagement with a landing page – how many people visited, how long they spent on the page, what device type they were on, and where they were referred from – PR & Comms teams can now track all the same metrics for select articles on Memo.

Details Page article data include:

Readership: the number of unique visitors to the article
Page views: the total number of article views across those readers
Average engaged time: the average time spent on the article
MRV: The dollar value of the article’s earned readership in paid-media terms, displayed for customers subscribed to MRV (Memo Readership Value) reporting
Time-series trends: these engagement metrics over time
Referring domains: the top 10 referring domains (e.g. facebook.com) for readership, page views, and MRV
Referral types: referring domains rolled up to high-level referral types: Search, Social, Direct (traffic that arrived on the article by typing/pasting the URL into a browser or, more often, via email/newsletter), Internal (traffic from within the publication’s site), and Other (traffic from external websites and news aggregators)
Device types: engagement data broken out by the device the reader was on (desktop, mobile, tablet)

This data answers your burning questions about article performance

While Memo’s insights are powered by macro trends from aggregated readership tracking, sometimes our customers have pressing questions about an individual article.

Why was an article so successful? Referring domains reveal the major traffic sources, helping identify contributors to high readership (e.g. virality on Reddit, high SEO in Google search, strong placement on Flipboard, etc). Traffic over time further indicates if the story is sustaining interest.

On the flip side, engagement data can guide next steps if you believe a placement underperformed. For example, take a glowing writeup of a brand with relatively low readership but high engaged time from the people who do read the article. The message is resonating, so it’s just a matter of amplifying the story on owned or paid channels (and using referring domains to track the results).

And in the case of a crisis event, readership over time can answer whether a story is picking up steam or dying down – crucial information in determining whether to issue a spokesperson response.

Details Pages also provide further evidence on the value of a great article

Zooming in on an individual article’s performance can offer compelling proof points to its value beyond readership or qualitative factors like message pull through.

An article’s average engaged time (90 seconds on average) drives home the power of editorial content to hold a reader’s attention far longer than other media.

Another example: For an article reviewing a product, high traffic from search indicates the placement reached a higher-intent audience. People considering a product likely googled it and looked for a review from a trusted publication.

And a third example: readership over time can signal when an article is sustaining interest, usually through strong SEO visibility. Being able to show off the long shelf-life of earned coverage – especially when juxtaposed with flash-in-the-pan ads – can further boost your stakeholders’ appreciation for the PR & Comms function. (For more on this theme, see PRWeek’s “Brands benefit from the long reach of a great story.”)

Access Details Pages from your Memo dashboard

Article Details Pages are available from publications that have given Memo full engagement-data access. An article has its own Details Page if there is an average engaged time indicator, which links out to a full Detail Page view.

Adding Article Details Pages to Memo’s platform furthers our mission to help brands harness the new possibilities of bringing data to the art of Communications. We look forward to seeing everything our clients do with it.